U.S. patent application number 15/613750 was filed with the patent office on 2018-12-06 for library of predefined shapes for additive manufacturing processes.
The applicant listed for this patent is United Technologies Corporation. Invention is credited to Ranadip Acharya, Sergei F. Burlatsky, Tahany Ibrahim El-Wardany, David Ulrich Furrer, Vijay Narayan Jagdale, John A. Sharon, Alexander Staroselsky.
Application Number | 20180348736 15/613750 |
Document ID | / |
Family ID | 62567365 |
Filed Date | 2018-12-06 |
United States Patent
Application |
20180348736 |
Kind Code |
A1 |
Sharon; John A. ; et
al. |
December 6, 2018 |
LIBRARY OF PREDEFINED SHAPES FOR ADDITIVE MANUFACTURING
PROCESSES
Abstract
A method includes accessing a first model defining a shape of a
part. The shape of the part is segregated into a plurality of
predefined shapes selected from a library of predefined shapes. The
predefined models for each of plurality of predefined shapes are
assembled into a second model defining the shape of the part. The
part is additively manufactured according to the second model.
Inventors: |
Sharon; John A.; (West
Hartford, CT) ; Jagdale; Vijay Narayan; (South
Windsor, CT) ; Burlatsky; Sergei F.; (West Hartford,
CT) ; Furrer; David Ulrich; (Marlborough, CT)
; El-Wardany; Tahany Ibrahim; (Bloomfield, CT) ;
Acharya; Ranadip; (Rocky Hill, CT) ; Staroselsky;
Alexander; (Avon, CT) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
United Technologies Corporation |
Farmington |
CT |
US |
|
|
Family ID: |
62567365 |
Appl. No.: |
15/613750 |
Filed: |
June 5, 2017 |
Current U.S.
Class: |
1/1 |
Current CPC
Class: |
B29C 64/386 20170801;
B29C 64/153 20170801; B33Y 10/00 20141201; B22F 3/1055 20130101;
Y02P 10/25 20151101; B33Y 30/00 20141201; G06F 30/00 20200101; B33Y
50/00 20141201; B22F 2003/1057 20130101; G05B 2219/49023 20130101;
G06F 30/23 20200101; G05B 19/4099 20130101 |
International
Class: |
G05B 19/4099 20060101
G05B019/4099; B29C 67/00 20060101 B29C067/00 |
Claims
1. A method comprising: accessing, by a processor, a first model
defining a shape of a part; segregating, by a processor, the shape
of the part into a plurality of predefined shapes selected from a
library of predefined shapes; assembling, by a processor,
predefined models for each of the plurality of predefined shapes
into a second model defining the shape of the part; and additively
manufacturing the part according to the second model.
2. The method of claim 1, wherein the predefined models for each of
the plurality of predefined shapes in the library of predefined
shapes includes instructions for an energy source power level, a
scan path, and a scan speed to be used during additive
manufacturing.
3. The method of claim 2, wherein the energy source power level,
the scan path, and the scan speed are dependent on the material
being used to additively manufacturing the part.
4. The method of claim 2, wherein the energy source power level,
the scan path, and the scan speed create an additively manufactured
part that has minimal to no defects or distortion.
5. The method of claim 2, wherein the energy source power level,
the scan path, and the scan speed are dependent on a temperature at
which the part is being additively manufactured.
6. The method of claim 1, wherein the plurality of predefined
shapes in the library of predefined shapes can include shapes
selected from the group consisting of rings, cylinders, tubes,
cuboids, cubes, prisms, pyramids, and combinations thereof.
7. The method of claim 1, wherein the plurality of predefined
shapes in the library of predefined shapes include shapes with
features selected from the group consisting of fillets, chamfers,
and combinations thereof.
8. The method of claim 1, and further comprising: simulating an
area surrounding an interface between adjacent predefined models in
the second model to determine if there are defects and/or
distortion in the area surrounding the interface.
9. The method of claim 8, and further comprising: adjusting the
second model in the area surrounding the interface between adjacent
predefined models to eliminate defects and distortion in the area
surrounding the interface.
10. The method of claim 9, wherein adjusting the second model in
the area surrounding the interface includes adjusting the energy
source power level, the scan path, and the scan speed for the
second model in the area surrounding the interface.
11. An additive manufacturing system comprising: at least one
processor; and computer-readable memory encoded with instructions
that, when executed by the at least one processor, cause the
additive manufacturing system to: access a first model defining a
shape of a part; segregate the shape of the part into a plurality
of predefined shapes selected from a library of predefined shapes;
assemble predefined models for each of the plurality of predefined
shapes into a second model defining the shape of the part; and
additively manufacture the part according to the second model.
12. The system of claim 11, wherein the predefined models for each
of the plurality of predefined shapes in the library of predefined
shapes includes instructions for an energy source power level, a
scan path, and a scan speed to be used during additive
manufacturing.
13. The system of claim 12, wherein the energy source power level,
the scan path, and the scan speed are dependent on the material
being used to additively manufacturing the part.
14. The system of claim 12, wherein the energy source power level,
the scan path, and the scan speed create an additively manufactured
part that has minimal to no defects or distortion.
15. The system of claim 12, wherein the energy source power level,
the scan path, and the scan speed are dependent on a temperature at
which the part is being additively manufactured.
16. The system of claim 11, wherein the plurality of predefined
shapes in the library of predefined shapes can include shapes
selected from the group consisting of rings, cylinders, tubes,
cuboids, cubes, prisms, pyramids, and combinations thereof.
17. The system of claim 11, wherein the plurality of predefined
shapes in the library of predefined shapes include shapes with
features selected from the group consisting of fillets, chamfers,
and combinations thereof.
18. The system of claim 11, wherein the computer-readable memory,
when executed by the at least one processor, will further cause the
additive manufacturing system to: simulate an area surrounding an
interface between adjacent predefined models in the second model to
determine if there are defects and/or distortion in the area
surrounding the interface.
19. The system of claim 18, wherein the computer-readable memory,
when executed by the at least one processor, will further cause the
additive manufacturing system to: adjust the second model in the
area surrounding the interface between adjacent predefined models
to eliminate defects and distortion in the area surrounding the
interface.
20. The system of claim 19, wherein adjusting the second model in
the area surrounding the interface includes adjusting the energy
source power level, the scan path, and the scan speed for the
second model in the area surrounding the interface.
Description
BACKGROUND
[0001] The present disclosure relates to additive manufacturing
processes, and in particular, to creating a model for additive
manufacturing processes.
[0002] Additive manufacturing is becoming increasingly popular as a
means for manufacturing parts with complex shapes. Additive
manufacturing allows a part to be manufactured layer-by-layer,
which allows complex design features to be included in the part
design when it was previously impossible. Additive manufacturing
processes generally include the following steps. First, a
three-dimensional model of the part is created using computer
software. The computer model is then sliced into a plurality of
layers. Information about the layers is then transmitted to an
additive manufacturing machine. The additive manufacturing machine
then builds the first layer of the part, and then builds the second
layer of the part on top of the first layer. This process continues
layer-by-layer to generatively build a part. Additive manufacturing
processes are becoming more widely adopted for the production of
complex near net shape parts, or parts that are close to their
final form. Despite the advances of the technology, it remains
difficult to repeatedly produce high quality parts with minimal
defects and distortion.
[0003] The current approach to creating a suitable computer-aided
design (CAD) model for additively manufacturing a part includes
creating a CAD model for the desired part geometry and cutting it
into layers. The additive manufacturing machine will typically
dictate a scan path for each layer. Depending on the material being
used, the additive manufacturing machine may select an energy
source power level and scan speed, or the energy source power level
and scan speed can be manually inputted into the additive
manufacturing machine. A first part is then additively manufactured
according to the CAD model, scan path, energy source power level,
and scan speed. The first part is then analyzed for defects and
distortion. The CAD model, scan path, energy source power level,
and scan speed can then be adjusted based on the analysis of the
first part, and a second part can be additively manufactured. This
process continues until a CAD model, scan path, energy source power
level, and scan speed is found that produces a part with minimal
defects and distortion. This is a very timely, expensive, and
resource intensive process.
[0004] There are two main issues with the current state of additive
manufacturing processes. The first issue is that there exists a
broad range of energy source power levels and scan speeds that can
be employed to fuse a feedstock powder. Depending on the particular
composition of the feedstock, certain combinations of power and
speed may be inadequate to fuse particles or be excessive, such
that the material boils or bubbles and causes pores to become
trapped in the build. The second issue is that the scanning path is
typically automatically generated by the additive manufacturing
system based on the CAD file of the part. This scan path is
de-coupled from the process parameters. This can cause defects and
distortion to occur during a build, as certain scan paths may
generate distortion and defects at certain energy source power
levels and/or scan speeds.
SUMMARY
[0005] A method includes accessing a first model defining a shape
of a part. The shape of the part is segregated into a plurality of
predefined shapes selected from a library of predefined shapes. The
predefined models for each of plurality of predefined shapes are
assembled into a second model defining the shape of the part. The
part is additively manufactured according to the second model.
[0006] An additive manufacturing system includes at least one
processor and computer-readable memory. The computer readable
memory is encoded with instructions that, when executed by the at
least one processor, cause the additive manufacturing system to
access a first model defining a shape of a part. The shape of the
part is segregated into a plurality of predefined shapes selected
from a library of predefined shapes. The predefined models for each
of plurality of predefined shapes are assembled into a second model
defining the shape of the part. The part is additively manufactured
according to the second model.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] FIG. 1 is a flowchart showing a process for additively
manufacturing a part.
[0008] FIG. 2 is a schematic diagram of a first model of the
part.
[0009] FIG. 3 is a schematic diagram of a plurality of predefined
models in a library of predefined shapes.
[0010] FIG. 4 is a schematic diagram of the first model of the part
after it has been segregated into a plurality of predefined
shapes.
[0011] FIG. 5 is a schematic diagram of a second model of the part
that has been assembled with predefined models from the library of
predefined shapes.
[0012] FIG. 6 is a schematic diagram of the second model of the
part showing an area surrounding an interface between adjacent
predefined models.
[0013] FIG. 7 is a perspective view of the part that has been
additively manufactured.
[0014] FIG. 8 is a schematic diagram of an additive manufacturing
system.
DETAILED DESCRIPTION
[0015] FIG. 1 is a flowchart showing a process for additively
manufacturing part 30. FIG. 1 includes steps 10, 12, 14, 16, 18,
and 20 to show a process for additively manufacturing part 30.
FIGS. 2-6 illustrate the steps seen in the flow chart is FIG. 1.
FIG. 2 is a schematic diagram of first model 30 of the part. FIG. 3
is a schematic diagram of predefined models 34, 36, 38, 40, 42, and
44 in library 32 of predefined shapes A, B, C, D, E, and F. FIG. 4
is a schematic diagram of first model 46 of the part after it has
been segregated into predefined shapes A and C. FIG. 5 is a
schematic diagram of second model 46 of the part that has been
assembled with predefined models 34 and 38 from library 32 of
predefined shapes A, B, C, D, E, and F. FIG. 6 is a schematic
diagram of second model 46 of the part showing area 50 surrounding
interface 48 between adjacent predefined models 34 and 38. FIG. 7
is a perspective view of part 52 that has been additively
manufactured.
[0016] Additive manufacturing processes manufacture parts
layer-by-layer. A typical additive manufacturing process includes
the following steps. First, a three-dimensional computer model of
the part is created. Next the computer model of the part is sliced
into a plurality of layers. Information about the first layer is
then transmitted to an additive manufacturing machine, and the
machine forms the first layer of the part. Included with the
information about the first layer is information regarding an
energy source power level, a scan path, and a scan speed to be used
to build the first layer. The energy source power level refers to
the intensity of the energy source that is used in the additive
manufacturing machine to solidify the part. The scan path refers to
the direction and path the energy source in the additive
manufacturing machine moves to solidify a layer of the part. The
scan speed refers to the speed with which the energy source moves
in the additive manufacturing machine to solidify the part.
[0017] After the first layer is built, information about the second
layer is then transmitted to the additive manufacturing machine,
including information regarding the energy source power level, the
scan path, and the scan speed. The machine forms the second layer
of the part on the first layer of the part. This process continues,
and each successive layer is built upon the previous layer to
create a part that has been manufactured layer-by-layer. Any
additive manufacturing process can be used to manufacture the part,
including direct metal laser sintering, electron beam freeform
fabrication, electron-beam melting, selective laser melting, or
selective laser sintering. Further, the exact steps taken to
generate the additively manufactured part can vary from the typical
steps.
[0018] Step 10 includes accessing first model 30 defining a shape
of a part, as shown in FIG. 2. First model 30 is a CAD model that
represents the shape of the part that is desired to be built with
additive manufacturing. First model 30 can be a model for a near
net shape part, or a part that is close to its final form. FIG. 2
shows an example of first model 30, in which first model 30 is a
model for a part with a cuboid portion and a prism portion. First
model 30 shown in FIG. 2 is for example purposes. In alternate
embodiments, first model 30 can be a model for a part with a more
complex shape and design.
[0019] Step 12 includes segregating the shape of the part into
predefined shapes A, B, C, D, E, and F, selected from library 32 of
predefined shapes A, B, C, D, E, and F, as shown in FIGS. 3-4.
Library 32 of predefined shapes A, B, C, D, E, and F is shown in
FIG. 3A. Library 32 can include any suitable shape, including
rings, cylinders, tubes, cubes, cuboids, prisms, pyramids, and any
other suitable shapes. As shown in FIG. 3, predefined shape A is a
cuboid; predefined shape B is a cylinder; predefined shape C is a
prism; predefined shape D is a tube; predefined shape E is a
pyramid; and predefined shape F is a cube. Predefined shapes A, B,
C, D, E, and F in library 32 can also include features such as
fillets and chamfers. Predefined shapes A, B, C, D, E, and F shown
in FIG. 3 are examples of shape that can be included in library 32.
Library 32 typically includes simple three-dimensional shapes that
form building blocks for more complex shapes and designs.
[0020] As shown in FIG. 4, first model 30 can be segregated into
predefined shape A, which is a cuboid, and predefined shape C,
which is a prism. First model 30 can be segregated into any number
of predefined shapes A, B, C, D, E, and F in library 32 in
alternate embodiments.
[0021] Step 14 includes assembling predefined models 34, 36, 38,
40, 42, and 44 for each of predefined shapes A, B, C, D, E, and F
in library 32 into second model 46 defining the shape of the part,
as shown in FIGS. 3 and 5. Library 32 includes predefined models
34, 36, 38, 40, 42, and 44 that correspond to predefined shapes A,
B, C, D, E, and F, respectively. Predefined models 34, 36, 38, 40,
42, and 44 are CAD models that have been cut into a plurality of
layers for use in additively manufacturing a part with the
predefined shape A, B, C, D, E, and F, respectively.
[0022] Predefined models 34, 36, 38, 40, 42, and 44 also include
instructions for an energy source power level, a scan path, and a
scan speed for the additive manufacturing machine to use during the
additive manufacturing process. The energy source power level
refers to the intensity of the energy source that is used in the
additive manufacturing machine to solidify the part. The scan path
refers to the direction and path the energy source in the additive
manufacturing machine moves to solidify a layer of the part. The
scan speed refers to the speed with which the energy source moves
in the additive manufacturing machine to solidify the part. Each of
predefined models 34, 36, 38, 40, 42, and 44 include instructions
for an energy source power level, a scan path, and a scan speed
that are known to result in additively manufactured parts with
minimal to no defects and distortion. The energy source power
level, the scan path, and the scan speed for each of predefined
models 34, 36, 38, 40, 42, and 44 can be dependent on the material
being used to additively manufacture the part and/or the
temperature at which the additive manufacturing is taking place.
Further, predefined models 34, 36, 38, 40, 42, and 44 can include a
range of energy source power levels, a range of scan paths, and a
range of scan speeds that are known to result in parts with minimal
to no defects and distortion, and a specific parameter for each can
be selected from the range of acceptable parameters.
[0023] Finite element simulations for thermal tracking and
computational fluid dynamics can be used to calibrate predefined
models 34, 36, 38, 40, 42, and 44. This enables predefined models
34, 36, 38, 40, 42, and 44 to be appropriately scaled (i.e., having
the same geometry but different size) for use parts of any
size.
[0024] As shown in FIG. 5, second model 46 of the part is formed
with predefined model 34 and predefined model 38. Second model 46
is a CAD model that represents the shape of the part that is
desired to be built with additive manufacturing. Second model 46
will have the same shape as first model 30. As shown in FIG. 4,
first model 30 of the part is formed with predefined shapes A and C
selected from library 32. As shown in FIG. 3, predefined models 34
and 38 correspond to predefined shapes A and C, respectively.
Predefined models 34 and 38 can be pulled from library 32 and
joined together to form second model 46 of the part, as shown in
FIG. 5. Second model 46 has the same shape as first model 30. Each
of predefined models 34 and 38 in second model 46 are broken into
layers for use in additive manufacturing the part. Further,
predefined models 34 and 38 in second model 46 include instructions
for an energy source power level, a scan path, and a scan speed for
the additive manufacturing machine to use while additively
manufacturing the part. The energy source power level, the scan
path, and the scan speed are specific to predefined models 34 and
38 and result in a part with minimal to no defects or distortion.
In alternate embodiments, second model 46 can have any shape and
can be built out of any number of predefined models 34, 36, 38, 40,
42, and 44.
[0025] Step 16 includes simulating area 50 surrounding interface 48
between adjacent predefined models 34 and 38 to determine if there
are defects in area 50 surrounding interface 48, as shown in FIG.
6. Second model 46, as shown in FIG. 6, includes interface 48
formed where predefined models 34 and 38 meet one another. In
alternate embodiments, second model 46 can have any shape and can
be built out of any number of predefined models 34, 36, 38, 40, 42,
and 44 and can include any number of interfaces 48.
[0026] Area 50 surrounds interface 48 and extends into a portion of
predefined models 34 and 38. Predefined models 34 and 38 include
instructions for an energy source power level, a scan path, and a
scan speed that are selected to form predefined shapes A and C,
respectively, with minimal to no defects or distortion. When
predefined models 34 and 38 are put together to form second model
46, the energy source power level, the scan path, and the scan
speed may not be suitable to form a part with minimal to no defects
or distortion in area 50 surrounding interface 48 between
predefined models 34 and 38. Thus, a simulation can be run in area
50 to determine if there are defects or distortion present in area
50 surrounding interface 48 when the energy source power level, the
scan path, and the scan speed for the predefined models are used.
Simulating area 50 can include creating a computational model for
finite element analysis (FEA) or analytical expressions of area
50.
[0027] Step 18 includes adjusting second model 46 in area 50
surrounding interface 48 to eliminate defects in area 50
surrounding interface 48. As discussed above in reference to step
16, a simulation is run in area 50 surrounding interface 48 to
determine if there are any defects or distortion in area 50
surrounding interface 48. If defects or distortion are found, the
energy source power level, the scan path, and the scan speed can be
adjusted in area 50 surrounding interface 48 in second model 46 as
needed to create a part with minimal to no defects or
distortion.
[0028] Step 20 includes additively manufacturing part 52 according
to second model 46, as shown in FIG. 7. After second model 46 is
deemed to be suitable for additively manufacturing a part with
minimal to no defects or distortion, part 52 can be additively
manufactured according to second model 46. As shown in FIG. 7, part
52 will have the shape and design of second model 46.
[0029] Additively manufacturing part 52 according to second model
46 will result in part 52 having minimal to no defects or
distortion. The formation of defects in parts that are additively
manufactured is mainly a function of the energy source power level,
the scan path, and the scan speed used to additively manufacture
the part. Pulling predefined models from a library of predefined
shapes to assemble a second model to be used to manufacture a part
allows for the part to have minimal to no defects or distortion, as
the predefined models include instructions for the energy source
power level, the scan path, and the scan speed to be used during
the additive manufacturing process so that the parts have minimal
to no defects or distortion.
[0030] Each of the predefined models will be created and tested to
ensure that they repeatedly and reliably produce parts with minimal
to no defects or distortion. Using the predefined models to
manufacture a part eliminates the need to manufacture the part,
analyze the part for defects and distortion, adjust the build
strategy, and then remanufacture the part and start the process
again. Rather, areas surrounding interfaces between the predefined
models can be simulated to test for defects and distortion and the
energy source power level, the scan path, and the scan speed can be
adjusted in the area surrounding the interfaces between the
predefined models as needed. Simulating an entire model for a part
is extremely time and cost prohibitive, hence why it is not
standard practice. However, having to only simulate an area
surrounding interfaces between the predefined models greatly
reduces the time and cost needed to simulate the part, allowing
defects and distortion in the areas surrounding the interfaces
between the predefined models to be identified.
[0031] Using predefined models from a library of predefined shapes
allows parts to be rapidly modeled and manufactured using additive
manufacturing processes. Further, using the predefined models
allows the additively manufactured parts to have a high quality
with minimal to no defects or distortion.
[0032] FIG. 8 is a schematic diagram of additive manufacturing
system 60. Additive manufacturing system 60 includes device 62,
database 64, controller 66, and additive manufacturing machine 68.
Device 62 includes processor(s) 70, communication device(s) 72,
input device(s) 74, output device(s) 76, and storage device(s) 78.
Storage device(s) 78 store computer-readable instructions that,
when executed by processor(s) 70, cause device 62 to perform
operations attributed herein to segregating module 80, assembly
module 82, simulation module 84, and adjustment module 86. That is,
while described herein as separate modules 80, 82, 84, and 86, in
some examples, functionality attributed herein to modules 80, 82,
84, and 86 can be distributed among any one or more of the
modules.
[0033] Additive manufacturing system 60 includes device 62 that
communicates with database 64 and controller 66. Device 62 can
communicate with database 64 and controller 66 with one or more
wired or wireless connections, or both. Controller 66 communicates
with and controls additive manufacturing machine 68. Controller 66
can communicate with additive manufacturing machine 68 with a wired
and/or wireless connection. Controller 66 can be separate from or
integrated with additive manufacturing machine 68. As such, device
62 communicates with additive manufacturing machine 68 via
communications routed through controller 66.
[0034] Device 62 can be any device capable of executing
computer-readable instructions defining a software program
implementing steps 10-18 as discussed above in reference to FIGS.
1-7. Examples of device 62 can include, but are not limited to,
laptop computers, mobile phones (including smartphones), tablet
computers, personal digital assistants (PDAs), desktop computers,
servers, mainframes, or other computing devices.
[0035] Database 64 can include one or more databases. Though
illustrated in the example of FIG. 8 as separate from and
communicatively coupled with device 62, in other examples, database
64 can be stored at storage devices 78 of device 62. Database 64
stores a library of predefined shapes, as discussed in reference to
FIG. 3 above. Database 64 can include one or more relational
databases, hierarchical databases, object-oriented databases,
multi-dimensional databases, or other types of databases configured
to store data useable by additive manufacturing system 60.
[0036] As illustrated in FIG. 8, device 62 can include processor(s)
70, communications device(s) 72, input device(s) 74, output
device(s) 76, and storage device(s) 78. However, in certain
examples, device 62 can include more or fewer components than
components 70, 72, 74, 76, and 78. For instance, in examples where
device 62 is a mobile or portable device such as a laptop computer,
device 62 may include additional components such as a battery that
provides power to components of device 62 during operation.
[0037] Processor(s) 70, in one example, are configured to implement
functionality and/or process instructions for execution within
device 70. For instance, processor(s) 70 can be capable of
processing instructions stored in storage device(s) 78. Examples of
processor(s) 70 can include any one or more of a microprocessor, a
controller, a digital signal processor (DSP), an application
specific integrated circuit (ASIC), a field-programmable gate array
(FPGA), or other equivalent discrete or integrated logic
circuitry.
[0038] Storage device(s) 78 can be configured to store information
within device 62 during operation. Storage device(s) 78, in some
examples, are described as computer-readable storage media. In some
examples, a computer-readable storage medium can include a
non-transitory medium. The term "non-transitory" can indicate that
the storage medium is not embodied in a carrier wave or a
propagated signal. In certain examples, a non-transitory storage
medium can store data that can, over time, change (e.g., in RAM or
cache). In some examples, storage device(s) 78 are a temporary
memory, meaning that a primary purpose of storage device(s) 78 is
not long-term storage. Storage device(s) 78, in some examples, are
described as volatile memory, meaning that storage device(s) 78 do
not maintain stored contents when power to device 62 is turned off.
Examples of volatile memories can include random access memories
(RAM), dynamic random access memories (DRAM), static random access
memories (SRAM), and other forms of volatile memories. In some
examples, storage device(s) 78 are used to store program
instructions for execution by processor(s) 70. Storage device(s)
78, in one example, are used by software or applications running on
device 62 (e.g., a software program implementing architecture 10)
to temporarily store information during program execution.
[0039] Storage device(s) 78, in some examples, also include one or
more computer-readable storage media. Storage device(s) 78 can be
configured to store larger amounts of information than volatile
memory. Storage device(s) 78 can further be configured for
long-term storage of information. In some examples, storage
device(s) 78 include non-volatile storage elements. Examples of
such non-volatile storage elements can include magnetic hard discs,
optical discs, floppy discs, flash memories, or forms of
electrically programmable memories (EPROM) or electrically erasable
and programmable (EEPROM) memories.
[0040] Device 62, in some examples, also includes communications
device(s) 74. Device 62, in one example, utilizes communication
device(s) 74 to communicate with external devices via one or more
networks, such as one or more wireless or wired networks or both.
Communications device(s) 74 can be a network interface card, such
as an Ethernet card, an optical transceiver, a radio frequency
transceiver, or any other type of device that can send and receive
information. Other examples of such network interfaces can include
Bluetooth, 3G, 4G, and WiFi radio computing devices as well as
Universal Serial Bus (USB).
[0041] Device 62, in some examples, also includes input device(s)
74. Input device(s) 74, in some examples, are configured to receive
input from a user. Examples of input device(s) 74 can include a
mouse, a keyboard, a microphone, a camera device, a
presence-sensitive and/or touch-sensitive display, or other type of
device configured to receive input from a user.
[0042] Output device(s) 76 can be configured to provide output to a
user. Examples of output device(s) 76 can include a display device,
a sound card, a video graphics card, a speaker, a cathode ray tube
(CRT) monitor, a liquid crystal display (LCD), a light emitting
diode (LED) display, an organic light emitting diode (OLED)
display, or other type of device for outputting information in a
form understandable to users or machines.
[0043] As illustrated in FIG. 8, storage device(s) 78 can include
segregating module 80, assembly module 82, simulation module 84,
and adjustment module 86. In operation, processor(s) 70 can access
a first model for a part that is to be additively manufactured,
such as a first model stored at storage devices 78 or another
computing device operatively coupled with device 62. The first
model defines a shape of the part. Segregating module 80, assembly
module 82, simulation module 84, and adjustment module 86,
executing on processor(s) 70, perform operations to operations to
additively manufacture a part according to a second model.
[0044] For example, segregating module 80 can segregate the first
model into a plurality of predefined shapes selected from the
library of predefined shapes in database 64. Assembly module 82 can
assemble predefined models from the library of predefined shapes in
database 64 into a second model. The predefined models from the
library of predefined shapes in database 64 include parameters for
use in additive manufacturing machine 68, including energy source
power level, scan path, and scan speed. Simulation module 84 can
simulate an area surrounding an interface between adjacent
predefined models to determine if there are defects in the area
surrounding the interface. If defects are found, adjustment module
86 can adjust the second model in the area surrounding the
interface. Adjustment module 86 can adjust the parameters for the
second model, including energy source power level, scan path, and
scan speed, as needed to eliminate defects and distortion in the
area surrounding the interface.
[0045] The second model can then be communicated by device 62
(e.g., via communication device(s) 72) to controller 66. Controller
66 can store the second model and provide instructions to additive
manufacturing machine on how to build the part. Accordingly, device
62 illustrates one example embodiment of a device that can execute
a software program including a plurality of segments that each
includes one or more modules implementing an interface that enables
direct communication between the respective module and modules that
are members of any other of the plurality of segments.
Discussion of Possible Embodiments
[0046] The following are non-exclusive descriptions of possible
embodiments of the present invention.
[0047] A method includes accessing, by a processor, a first model
defining a shape of a part. The shape of the part is segregated, by
a processor, into a plurality of predefined shapes selected from a
library of predefined shapes. Predefined models for each of the
plurality of predefined shapes are assembled, by a processor, into
a second model defining the shape of the part. The part is
additively manufactured according to the second model.
[0048] The method of the preceding paragraph can optionally
include, additionally and/or alternatively, any one or more of the
following features, configurations and/or additional
components:
[0049] Wherein the predefined models for each of the plurality of
predefined shapes in the library of predefined shapes includes
instructions for an energy source power level, a scan path, and a
scan speed to be used during additive manufacturing.
[0050] Wherein the energy source power level, the scan path, and
the scan speed are dependent on the material being used to
additively manufacturing the part.
[0051] Wherein the energy source power level, the scan path, and
the scan speed create an additively manufactured part that has
minimal to no defects or distortion.
[0052] Wherein the energy source power level, the scan path, and
the scan speed are dependent on a temperature at which the part is
being additively manufactured.
[0053] Wherein the plurality of predefined shapes in the library of
predefined shapes can include shapes selected from the group
consisting of rings, cylinders, tubes, cuboids, cubes, prisms,
pyramids, and combinations thereof.
[0054] Wherein the plurality of predefined shapes in the library of
predefined shapes include shapes with features selected from the
group consisting of fillets, chamfers, and combinations
thereof.
[0055] The method further includes simulating an area surrounding
an interface between adjacent predefined models in the second model
to determine if there are defects and/or distortion in the area
surrounding the interface.
[0056] The method further includes adjusting the second model in
the area surrounding the interface between adjacent predefined
models to eliminate defects and distortion in the area surrounding
the interface.
[0057] Wherein adjusting the second model in the area surrounding
the interface includes adjusting the energy source power level, the
scan path, and the scan speed for the second model in the area
surrounding the interface.
[0058] An additive manufacturing system includes at least one
processor, and computer-readable memory. The computer-readable
memory is encoded with instructions that, when executed by the at
least one processor, cause the additive manufacturing system to
access a first model defining a shape of a part. The shape of the
part is segregated into a plurality of predefined shapes selected
from a library of predefined shapes. The predefined models for each
of the plurality of predefined shapes are assembled into a second
model defining the shape of the part. The part is additive
manufactured according to the second model.
[0059] The additive manufacturing system of the preceding paragraph
can optionally include, additionally and/or alternatively, any one
or more of the following features, configurations and/or additional
components:
[0060] Wherein the predefined models for each of the plurality of
predefined shapes in the library of predefined shapes includes
instructions for an energy source power level, a scan path, and a
scan speed to be used during additive manufacturing.
[0061] Wherein the energy source power level, the scan path, and
the scan speed are dependent on the material being used to
additively manufacturing the part.
[0062] Wherein the energy source power level, the scan path, and
the scan speed create an additively manufactured part that has
minimal to no defects or distortion.
[0063] Wherein the energy source power level, the scan path, and
the scan speed are dependent on a temperature at which the part is
being additively manufactured.
[0064] Wherein the plurality of predefined shapes in the library of
predefined shapes can include shapes selected from the group
consisting of rings, cylinders, tubes, cuboids, cubes, prisms,
pyramids, and combinations thereof.
[0065] Wherein the plurality of predefined shapes in the library of
predefined shapes include shapes with features selected from the
group consisting of fillets, chamfers, and combinations
thereof.
[0066] Wherein the computer-readable memory, when executed by the
at least one processor, will further cause the additive
manufacturing system to simulate an area surrounding an interface
between adjacent predefined models in the second model to determine
if there are defects and/or distortion in the area surrounding the
interface.
[0067] Wherein the computer-readable memory, when executed by the
at least one processor, will further cause the additive
manufacturing system to adjust the second model in the area
surrounding the interface between adjacent predefined models to
eliminate defects and distortion in the area surrounding the
interface.
[0068] Wherein adjusting the second model in the area surrounding
the interface includes adjusting the energy source power level, the
scan path, and the scan speed for the second model in the area
surrounding the interface.
[0069] While the invention has been described with reference to an
exemplary embodiment(s), it will be understood by those skilled in
the art that various changes may be made and equivalents may be
substituted for elements thereof without departing from the scope
of the invention. In addition, many modifications may be made to
adapt a particular situation or material to the teachings of the
invention without departing from the essential scope thereof.
Therefore, it is intended that the invention not be limited to the
particular embodiment(s) disclosed, but that the invention will
include all embodiments falling within the scope of the appended
claims.
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